Over 85% of all working age adults now own smartphones in the United States (U.S.). Essentially all mobile devices (e.g., mobile phone devices, e.g., smartphones) can accurately track location using GPS chips. Many applications (apps) on mobile devices make use of this location data to provide their services. Terms of use for many of these applications allow the application to capture information about usage including location data, and to use and resell this mobile device geolocation data. As a result, it is now possible to purchase mobile device geolocation data from cell phones. In the US, these data are available for well over 10% of all smartphones, and coverage is steadily increasing. Global availability of mobile device geolocation data is also growing rapidly.
FIG. 6 shows an illustrative example 600 of the flow of mobile device geolocation data from a GPS chip of a mobile device to a company. GPS chip 620 determines the position of a mobile device based on signals received from GPS satellites 610. Smartphone App 630 can use this information to provide services to a user of the mobile device. A company (e.g., a data broker, e.g., a telecommunications company, e.g., a technology company) 640 can acquire this location data from multiple mobile devices and offer it for sale.
Mobile device geolocation data can also be obtained from the triangulation of signals from telecommunications towers (e.g., cellular towers) and known locations of WIFI spots. GPS chips can provide significantly more accurate tracking of device location than is possible using other means such as by triangulating device positions from network-based telecommunications data based on signal intensities measured at multiple cellular towers. For example, FIG. 7 shows an illustrative example 700 of the triangulation of a position for mobile device 710 based on signal strengths at telecommunication towers 720.
Mobile device geolocation data typically includes a unique device identifier (UID) for each mobile device along with a sequence of device positions (e.g., latitude and longitude pairs), each with a corresponding timestamp. Generally, geolocation data may include additional information such as a UID type, a source identifier, a device type, and an accuracy. Mobile device geolocation data are collected at a wide range of frequencies, from seconds to minutes to hours depending on the source. Some sources (e.g., smartphone Apps, e.g., software development kits (SDKs), e.g., operating systems) use irregular frequencies to minimize battery usage. For example, new location pings may only be generated when a user opens a given App or begins to move and/or settles in a new location.
The commercial use of mobile device geolocation data is growing. However, commercially available analysis has currently been limited to applications such as counting customers at business locations and estimating the characteristics of vehicle traffic.
In both the U.S. and the Europe, approximately 70% of all freight is carried by truck. Currently, no comprehensive granular (e.g., detailed) data are available about this freight movement anywhere for any price. This data is not presently available because there are no detailed reporting requirements for trucking freight movements, and the trucking industry is highly fractured thereby diffusing the data across thousands of companies. Consequently, industrial freight movement, a critical precursor and indicator of company and customer economic activity, remains obscure at all but the most macro levels. No current method exists to accurately measure freight movement.
In the US, approximately half of all freight is transported by “private carriers”. Private carriers are companies in businesses other than trucking that move their own freight in their own trucks. There are private carriers in essentially any industry which moves freight. There are so few reporting requirements for this type of freight movement that it is completely ignored in the U.S. government's Economic Census produced every 5 years and in its annual Economic Survey. Company-specific historical data, let alone real-time company specific data, are unavailable.
For-hire carriers are companies whose primary business is selling trucking services. For-hire carriers can be segmented into many sub-industries such as: package carriers, truckload (TL) carriers, less-than-truckload (LTL) carriers, drayage carriers, and specialty carriers (e.g., carriers using refrigerated trucks, flatbed trucks, trucks for transporting motor vehicles, trucks for transporting household goods, or the like). Except for package carriers—which are largely dominated by large corporate entities—each of these sub-industries is highly fractured and has many competing companies. Some sub-industries such as truckload carriers have individual owner-operators and very small companies that successfully compete in the marketplace and represent a significant portion of the sub-industry. While some historical macro information can be obtained about different sub-industries and some information can be learned from public carriers, no detailed or real-time information about freight movement is available in the marketplace.
Most attempts at providing real-time monitoring of freight movement require freight operators to install dedicated tracking devices on each truck. However, this approach is costly, and companies are very reluctant to share this data with third parties. Freight vehicle traffic can potentially be estimated from telecommunications data acquired from telecommunications towers (e.g., from estimated cellphone positions based on signal triangulation between cell towers such as that depicted in FIG. 7). However, telecommunications data provide very low-accuracy estimates of cellphone positions. Positions estimated from telecommunications data are generally only accurate to within the area of a zip code. Because of their low accuracy, positions derived from telecommunications data cannot be used for analysis beyond gross estimates of regional traffic. Therefore, there exists a need for improved systems and methods for monitoring the movement of freight.